A deterministic predictive traffic signal control model in intelligent transportation and geoinformation systems
Vladislav Myasnikov, IPSI RAS – Branch of the FSRC “Crystallography and Photonics” RAS, Anton Agafonov, Alexander Yumaganov
Abstract
In this paper, we propose a traffic signal control method in intelligent transportation and geoinformation systems, based on a deterministic predictive model. The method provides adaptive control based on traffic data, including data from connected and autonomous vehicles. The proposed method is compared with the state-of-the-art traffic signal control solutions: empirical control algorithms and reinforcement learning-based control methods. An advantage of the proposed method is shown and directions of further research are outlined.
Topics & Concepts
Intelligent transportation systemComputer scienceSIGNAL (programming language)Reinforcement learningModel predictive controlControl (management)Control systemGeographic information systemControl engineeringReal-time computingEngineeringArtificial intelligenceTransport engineeringGeographyRemote sensingProgramming languageElectrical engineeringTraffic control and managementTraffic Prediction and Management TechniquesTransportation Systems and Logistics